ArticleFrontiers in neuroscience2023
At-home sleep monitoring using generic ear-EEG.
Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Towards neuromorphic neurotechnologies: integrating brain-inspired computing with brain-computer interfaces.npj biomedical innovations · 2026Review
- Smart Wearable EEG Devices: A Review of Lightweight, Multi-Sensor Systems for Sleep and Everyday Neurophysiology.Biosensors · 2026Review
- Recent Progress in In-Ear EEG Technology and Its Emerging Real-World Applications: A Review.Micromachines · 2026Review
- Evaluating the performance of wearable EEG sleep monitoring devices: a meta-analysis approach.npj biomedical innovations · 2025Article
- Forehead and In-Ear EEG Acquisition and Processing: Biomarker Analysis and Memory-Efficient Deep Learning Algorithm for Sleep Staging with Optimized Feature Dimensionality.Sensors (Basel, Switzerland) · 2025Article
- Technological Advances and Medical Applications of Implantable Electronic Devices: From the Heart, Brain, and Skin to Gastrointestinal Organs.Biosensors · 2025Review
- The Next Frontier in Brain Monitoring: A Comprehensive Look at In-Ear EEG Electrodes and Their Applications.Sensors (Basel, Switzerland) · 2025Review
- Ear-EEG sleep monitoring data sets.Scientific data · 2025Article
- A deep learning-enabled smart garment for accurate and versatile monitoring of sleep conditions in daily life.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Home-Based sensing of the nervous system with clinical neurophysiology technologies: IFCN handbook chapter.Clinical neurophysiology practice · 2025Review
- Hearables: Bioelectronics technological challenges and opportunities.Wearable technologies · 2025Review
- Evaluating the Electroencephalographic Signal Quality of an In-Ear Wearable Device.Sensors (Basel, Switzerland) · 2024Article
- Remote Wearable Neuroimaging Devices for Health Monitoring and Neurophenotyping: A Scoping Review.Biomimetics (Basel, Switzerland) · 2024Article
- Comparison analysis between standard polysomnographic data and in-ear-electroencephalography signals: a preliminary study.Sleep advances : a journal of the Sleep Research Society · 2024Article
- Signal quality evaluation of an in-ear EEG device in comparison to a conventional cap system.Frontiers in neuroscience · 2024Article
- Advancements in Wearable EEG Technology for Improved Home-Based Sleep Monitoring and Assessment: A Review.Biosensors · 2023Review
- Toward Personalized Medicine Approaches for Parkinson Disease Using Digital Technologies.JMIR formative research · 2023Review
- A Versatile In-Ear Biosensing System and Body-Area Network for Unobtrusive Continuous Health Monitoring.IEEE transactions on biomedical circuits and systems · 2023Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: A device comprising two generic earpieces with embedded dry electrodes for ear-centered electroencephalography (ear-EEG) was developed. The objective was to provide ear-EEG based sleep monitoring to a wide range of the population without tailoring the device to the individual. Methods: To validate the device ten healthy subjects were recruited for a 12-night sleep study. The study was divided into two parts; part A comprised two nights with both ear-EEG and polysomnography (PSG), and part B comprised 10 nights using only ear-EEG. In addition to the electrophysiological measurements, subjects filled out a questionnaire after each night of sleep. Results: The subjects reported that the ear-EEG system was easy to use, and that the comfort was better in part B. The performance of the system was validated by comparing automatic sleep scoring based on ear-EEG with PSG-based sleep scoring performed by a professional trained sleep scorer. Cohen's kappa was used to assess the agreement between the manual and automatic sleep scorings, and the study showed an average kappa value of 0.71. The majority of the 20 recordings from part A yielded a kappa value above 0.7. The study was compared to a companioned study conducted with individualized earpieces. To compare the sleep across the two studies and two parts, 7 different sleeps metrics were calculated based on the automatic sleep scorings. The ear-EEG nights were validated through linear mixed model analysis in which the effects of equipment (individualized vs. generic earpieces), part (PSG and ear-EEG vs. only ear-EEG) and subject were investigated. We found that the subject effect was significant for all computed sleep metrics. Furthermore, the equipment did not show any statistical significant effect on any of the sleep metrics. Discussion: These results corroborate that generic ear-EEG is a promising alternative to the gold standard PSG for sleep stage monitoring. This will allow sleep stage monitoring to be performed in a less obtrusive way and over longer periods of time, thereby enabling diagnosis and treatment of diseases with associated sleep disorders.
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